SafeRoute: Crime Zone Analysis Using Machine Learning
Peer‑reviewed conference work proposing a system to extract crime-related information from online sources, identify crime-prone areas, and support safer route suggestions.
Highlights
- App: Built an Android application in Java to provide insights into crime-prone areas, suggest safety precautions, and expose emergency contact options.
- Clustering: Applied K‑Means clustering and the elbow method in Python to compute “danger indices” for locations.
- Routing: Used Google Maps API to recommend safer routes based on the computed indices.